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  1. Bridging Mainstream and Formal Ontology: A Causality-Based Upper Ontology in Dietrich of Freiberg.Luis M. Augusto - 2021 - Journal of Knowledge Structures and Systems 2 (2):35.
    Ontologies are some of the most central constructs in today's large plethora of knowledge technologies, namely in the context of the semantic web. As their coinage indicates, they are direct heirs to the ontological investigations in the long Western philosophical tradition, but it is not easy to make bridges between them. Contemporary ontological commitments often take causality as a central aspect for the ur-segregation of entities, especially in scientific upper ontologies; theories of causality and philosophical ontological investigations often go hand-in-hand, (...)
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  • From Symbols to Knowledge Systems: A. Newell and H. A. Simon's Contribution to Symbolic AI.Luis M. Augusto - 2021 - Journal of Knowledge Structures and Systems 2 (1):29 - 62.
    A. Newell and H. A. Simon were two of the most influential scientists in the emerging field of artificial intelligence (AI) in the late 1950s through to the early 1990s. This paper reviews their crucial contribution to this field, namely to symbolic AI. This contribution was constituted mostly by their quest for the implementation of general intelligence and (commonsense) knowledge in artificial thinking or reasoning artifacts, a project they shared with many other scientists but that in their case was theoretically (...)
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  • Can Knowledge Be Quantified and Qualified?Farshad Badie - 2021 - Journal of Knowledge Structures and Systems 1 (2):63-67.
    The opinion defended in this paper is that the interrelationships between the phenomena of data and information can provide a strong basis for analyzing knowledge as a quantified and qualified construction. As other models (e.g., Augusto’s General Theory of Knowledge) suggest, it is important to distinguish knowledge from both data and information in the complicated trio composed of data, information, and knowledge (DIK). However, data and information can be combined into informative data. Taking into account quantified and qualified informative data, (...)
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  • DNAOS for KREMMS: A Distributed Platform for Knowledge Resource Entitlement, Modeling, Management, and Sharing.Andre Cusson - 2020 - Journal of Knowledge Structures and Systems 1 (1):117-133.
    This article is a knowledge technology case study of DNAOS, a distributed platform for Knowledge Resource Entitlement, Modeling, Management, and Sharing (KREMMS). Some historical aspects of its design, development, and release are briefly discussed, after which the DNAOS technology is commented upon from the specific viewpoint of KREMMS. At the core of this platform is the conception of knowledge as a natural phenomenon, which conception is reflected in the ontology of this technology: Fundamental knowledge structures and structuring principles, believed to (...)
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